SOTAVerified

Pose Estimation

Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.

A common benchmark for this task is MPII Human Pose

( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )

Papers

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Showing 701–750 of 4228 papers

TitleStatusHype
Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrieval—0
SUPER: Seated Upper Body Pose Estimation using mmWave Radars—0
Active Human Pose Estimation via an Autonomous UAV Agent—0
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review—0
EPOCH: Jointly Estimating the 3D Pose of Cameras and Humans—0
Human Modelling and Pose Estimation Overview—0
Towards Human-Level 3D Relative Pose Estimation: Generalizable, Training-Free, with Single ReferenceCode0
Automatic infant 2D pose estimation from videos: comparing seven deep neural network methods—0
High-resolution open-vocabulary object 6D pose estimation—0
Breaking the Frame: Visual Place Recognition by Overlap PredictionCode1
Efficient Human Pose Estimation: Leveraging Advanced Techniques with MediaPipeCode0
Investigating the impact of 2D gesture representation on co-speech gesture generation—0
Benchmarking Monocular 3D Dog Pose Estimation Using In-The-Wild Motion Capture Data—0
PoseBench: Benchmarking the Robustness of Pose Estimation Models under Corruptions—0
An Efficient yet High-Performance Method for Precise Radar-Based Imaging of Human Hand Poses—0
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction—0
NeRF-Feat: 6D Object Pose Estimation using Feature Rendering—0
CNN Based Flank Predictor for Quadruped Animal Species—0
Head Pose Estimation and 3D Neural Surface Reconstruction via Monocular Camera in situ for Navigation and Safe Insertion into Natural Openings—0
Overlap Suppression Clustering for Offline Multi-Camera People Tracking—0
SeamPose: Repurposing Seams as Capacitive Sensors in a Shirt for Upper-Body Pose Tracking—0
Matching Query Image Against Selected NeRF Feature for Efficient and Scalable Localization—0
Domain Generalization for In-Orbit 6D Pose Estimation—0
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference—0
MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor PerceptionCode0
Galibr: Targetless LiDAR-Camera Extrinsic Calibration Method via Ground Plane Initialization—0
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences—0
OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics—0
MeshPose: Unifying DensePose and 3D Body Mesh reconstructionCode1
ImageNet3D: Towards General-Purpose Object-Level 3D UnderstandingCode1
Deep Transformer Network for Monocular Pose Estimation of Ship-Based UAVCode0
Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization—0
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language TasksCode5
IFTD: Image Feature Triangle Descriptor for Loop Detection in Driving ScenesCode1
From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment LayersCode1
SPIN: Spacecraft Imagery for NavigationCode1
Realistic Data Generation for 6D Pose Estimation of Surgical InstrumentsCode0
SignMusketeers: An Efficient Multi-Stream Approach for Sign Language Translation at Scale—0
Multicam-SLAM: Non-overlapping Multi-camera SLAM for Indirect Visual Localization and NavigationCode1
Real-Time Spacecraft Pose Estimation Using Mixed-Precision Quantized Neural Network on COTS Reconfigurable MPSoCCode0
Omni6DPose: A Benchmark and Model for Universal 6D Object Pose Estimation and Tracking—0
GLACE: Global Local Accelerated Coordinate EncodingCode2
Hi5: 2D Hand Pose Estimation with Zero Human Annotation—0
Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation on Edge Devices—0
HPE-CogVLM: Advancing Vision Language Models with a Head Pose Grounding Task—0
3D WholeBody Pose Estimation based on Semantic Graph Attention Network and Distance Information—0
A Robust Filter for Marker-less Multi-person Tracking in Human-Robot Interaction ScenariosCode0
Equivariant amortized inference of poses for cryo-EM—0
CapeX: Category-Agnostic Pose Estimation from Textual Point ExplanationCode1
Estimating Human Poses Across Datasets: A Unified Skeleton and Multi-Teacher Distillation Approach—0
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All datasetsCOCO test-devMPII Human PoseOCHumanLeeds Sports PosesCrowdPoseCOCO val2017AICCOCO (Common Objects in Context)InLocITOP front-viewJ-HMDBMPII Single Person

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1yoloposeAP5090.3—Unverified
2ViTPose (ViTAE-G, ensemble)AP81.1—Unverified
3ViTPose (ViTAE-G)AP80.9—Unverified
4UDP-Pose-PSA(384x288)AP79.5—Unverified
5PoseBH-HAP79.5—Unverified
64xRSN-50 (ensemble)AP79.2—Unverified
7UDP-Pose-PSA(256x192)AP78.9—Unverified
8CCM+AP78.9—Unverified
94xRSN-50AP78.6—Unverified
10PCT (256x256)AP78.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PCT (swin-l, test set)PCKh-0.594.3—Unverified
2Soft-gated Skip ConnectionsPCKh-0.594.1—Unverified
3Cascade Feature AggregationPCKh-0.593.9—Unverified
4PCT (swin-b, test set)PCKh-0.593.8—Unverified
5TransPosePCKh-0.593.5—Unverified
6UniHCP (FT)PCKh-0.593.2—Unverified
74xRSN-50PCKh-0.593—Unverified
8UniPosePCKh-0.592.7—Unverified
9MSPNPCKh-0.592.6—Unverified
10Spatial ContextPCKh-0.592.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTPose (ViTAE-G, GT bounding boxes)Test AP93.3—Unverified
2UniHCP (direct eval)Test AP87.4—Unverified
3PoseBH-HTest AP87—Unverified
4RTMPose(RTMPose-l, GT bounding boxes)Test AP80.3—Unverified
5TransPose-HValidation AP62.3—Unverified
6BBox-Mask-Pose 2xTest AP48.3—Unverified
7BUCTD (CID-W32)Test AP47.2—Unverified
8HQNet (ViT-L)Test AP45.6—Unverified
9CID (HRNet-W48)Test AP45—Unverified
10MaskPose-bTest AP45—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPosePCK99.5—Unverified
2Soft-gated Skip ConnectionsPCK94.8—Unverified
3UniPosePCK94.5—Unverified
4Residual Hourglass + ASR + AHOPCK94.5—Unverified
5Chou et al. arXiv'17PCK94—Unverified
6Pyramid Residual Modules (PRMs)PCK93.9—Unverified
7Stacked hourglass + Inception-resnetPCK93.9—Unverified
8Multi-Context AttentionPCK92.6—Unverified
9FPDPCK90.8—Unverified
10Part heatmap regression (ResNet-152)PCK90.7—Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD-W48 (w/cond. input from PETR, and generative sampling)AP78.5—Unverified
2ViTPose-GAP78.3—Unverified
3BUCTD-W48 (w/cond. input from PETR)AP76.7—Unverified
4SwinV2-L 1K-MIMAP75.5—Unverified
5SwinV2-B 1K-MIMAP74.9—Unverified
6BUCTD-W48AP72.9—Unverified
7OpenPifPafAP70.5—Unverified
8MIPNet (HRNet-W48)AP70—Unverified
9KAPAO-LAP68.9—Unverified
10KAPAO-MAP67.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CCNet (ViTPose-B_GT-bbox_256x192)AP78.1—Unverified
2MogaNet-B (384x288)AP77.3—Unverified
3ViTPose-B (Single-task_GT-bbox_256x192)AP77.3—Unverified
4MogaNet-S (384x288)AP76.4—Unverified
5Bias (HRNet_256x192)AP75.8—Unverified
6ViTPose-B (Single-task_Det-bbox_256x192)AP75.8—Unverified
7HRNet (256x192)AP75.3—Unverified
8MogaNet-S (256x192)AP74.9—Unverified
9MogaNet-T (256x192)AP73.2—Unverified
10RLE (256x192)AP71.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Hulk(Finetune, ViT-L)AP37.1—Unverified
2Hulk(Finetune, ViT-B)AP35.6—Unverified
3HRFormer (HRFomer-B)AP34.4—Unverified
4UniHCP (finetune)AP33.6—Unverified
5HRNet (HRNet-w48 )AP33.5—Unverified
6HRNet (HRNet-w32)AP32.3—Unverified
7HRFormer (HRFomer-S)AP31.6—Unverified
8SimpleBaseline (ResNet-152)AP29.9—Unverified
9SimpleBaseline (ResNet-101)AP29.4—Unverified
10SimpleBaseline (ResNet-50)AP28—Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD (PETR, with generative sampling)APL83.7—Unverified
2OmniPose (WASPv2)AP79.5—Unverified
3MetaPrompt-SDAP79—Unverified
4Hulk(Finetune, ViT-L)AP78.7—Unverified
5BUCTD (PETR, with generative sampling)AP77.8—Unverified
6Hulk(Finetune, ViT-B)AP77.5—Unverified
7I²R-Net (1st stage:HRFormer-B)AP77.3—Unverified
8PATH (Partial FT)AP77.1—Unverified
9SOLIDER (swin-B)AP76.6—Unverified
10PEFORMER-Xcit-dino-p8AP72.6—Unverified
#ModelMetricClaimedVerifiedStatus
1GIM-DKMDUC1-Acc@0.25m,10°57.1—Unverified
2GIM-LoFTRDUC1-Acc@0.25m,10°54.5—Unverified
3GIM-SuperGlueDUC1-Acc@0.25m,10°53.5—Unverified
4DKMDUC1-Acc@0.25m,10°51.5—Unverified
5SuperGlueDUC1-Acc@0.25m,10°49—Unverified
6LoFTRDUC1-Acc@0.25m,10°47.5—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaPoseMean mAP93.38—Unverified
2DECA-D3Mean mAP88.75—Unverified
3V2V-PoseNetMean mAP88.74—Unverified
4A2JMean mAP88—Unverified
5RENMean mAP84.9—Unverified
6Multi-task learning + viewpoint invarianceMean mAP77.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SimpleBaseline + HANetMean PCK@0.299.6—Unverified
2DeciWatchMean PCK@0.299—Unverified
3LSTM PMMean PCK@0.293.6—Unverified
4CPMMean PCK@0.291.9—Unverified
5UniTrack_i18Mean PCK@0.280.5—Unverified
#ModelMetricClaimedVerifiedStatus
14xRSN-50PCKh@0.593—Unverified
2RefinePCKh@0.592.1—Unverified
3EfficientPose IVPCKh@0.591.2—Unverified
4OpenPosePCKh@0.588.8—Unverified
5Adversarial LearningPCKh@0.588.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPoseMean PCK@0.299.4—Unverified
2UniPose-LSTMMean PCK@0.299.3—Unverified
3LSTM PMMean PCK@0.297.7—Unverified
4Thin-SlicingMean PCK@0.296.5—Unverified
5Iqbal et al.Mean PCK@0.281.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DP-RCNN-DeepLab (ResNet-101)AP68—Unverified